A barcode widely used over the industries was recently designed to increase product management efficiency and has made a great achievement in the sector of the retail market. Based thereon, it is used for a variety of applications even in the fields of other industries. In the past, it was common to use, as devices for reading the barcode, barcode-exclusive recognition devices such as a laser scanner, but thanks to the recent spread of the use of mobile terminals, a method for recognizing the barcode by using cameras equipped on mobile terminals has been introduced.
The cameras on such mobile terminals, however, have generally lower resolution than the laser scanner and they tend to have a serious level of noise. Accordingly, the serious blur of the barcode image taken therefor caused poor barcode reading.
In order to solve the blur problem, several technologies have been presented, among which the representative technology is to estimate the accurate point spread function (PSF) and noise-to-signal ratio of a camera and perform deblurring of a barcode image based on the estimation. However, the technology is not applicable only on the case that the PSF distribution is consistent with a mathematically well-defined Gaussian distribution or a disk distribution but also generally requires a strong level of an image signal sample that may not be adopted on such mobile terminals. For the reason, in reality, it could not be used to improve the blurring of the barcode image taken by camera modules of the general mobile terminals.
Accordingly, the applicant of the present invention came to develop a technology to support deblurring of an inputted barcode image more effectively even in a general mobile terminal environment that has a complicated optical transfer function (OTF) which cannot be approximated to the Gaussian distribution or the disk distribution.